| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 134 | | tagDensity | 0.015 | | leniency | 0.03 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2100 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 85.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2100 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "familiar" | | 3 | "porcelain" | | 4 | "pulse" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 135 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 135 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 267 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2100 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 86 | | wordCount | 1201 | | uniqueNames | 11 | | maxNameDensity | 3 | | worstName | "Eva" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Aurora | 35 | | Eva | 36 | | Cardiff | 1 | | Silas | 7 |
| | persons | | 0 | "Carter" | | 1 | "Blackwood" | | 2 | "Aurora" | | 3 | "Eva" | | 4 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Cardiff" |
| | globalScore | 0.001 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2100 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 267 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 198 | | mean | 10.61 | | std | 10.13 | | cv | 0.955 | | sampleLengths | | 0 | 54 | | 1 | 57 | | 2 | 50 | | 3 | 4 | | 4 | 18 | | 5 | 25 | | 6 | 34 | | 7 | 9 | | 8 | 41 | | 9 | 1 | | 10 | 10 | | 11 | 23 | | 12 | 11 | | 13 | 11 | | 14 | 13 | | 15 | 10 | | 16 | 10 | | 17 | 10 | | 18 | 3 | | 19 | 10 | | 20 | 9 | | 21 | 5 | | 22 | 9 | | 23 | 4 | | 24 | 7 | | 25 | 19 | | 26 | 10 | | 27 | 4 | | 28 | 9 | | 29 | 15 | | 30 | 10 | | 31 | 37 | | 32 | 4 | | 33 | 7 | | 34 | 16 | | 35 | 4 | | 36 | 9 | | 37 | 5 | | 38 | 27 | | 39 | 2 | | 40 | 6 | | 41 | 2 | | 42 | 2 | | 43 | 16 | | 44 | 2 | | 45 | 14 | | 46 | 3 | | 47 | 3 | | 48 | 7 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 203 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 267 | | ratio | 0.004 | | matches | | 0 | "The limp stayed the same; the sound had grown longer." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1205 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 31 | | adverbRatio | 0.025726141078838173 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0016597510373443983 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 267 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 267 | | mean | 7.87 | | std | 5.45 | | cv | 0.693 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 20 | | 3 | 15 | | 4 | 24 | | 5 | 1 | | 6 | 1 | | 7 | 7 | | 8 | 9 | | 9 | 20 | | 10 | 13 | | 11 | 9 | | 12 | 8 | | 13 | 4 | | 14 | 2 | | 15 | 9 | | 16 | 7 | | 17 | 25 | | 18 | 6 | | 19 | 20 | | 20 | 8 | | 21 | 9 | | 22 | 13 | | 23 | 10 | | 24 | 18 | | 25 | 1 | | 26 | 10 | | 27 | 4 | | 28 | 12 | | 29 | 7 | | 30 | 11 | | 31 | 11 | | 32 | 13 | | 33 | 10 | | 34 | 10 | | 35 | 5 | | 36 | 5 | | 37 | 3 | | 38 | 10 | | 39 | 9 | | 40 | 5 | | 41 | 9 | | 42 | 4 | | 43 | 7 | | 44 | 5 | | 45 | 14 | | 46 | 6 | | 47 | 4 | | 48 | 4 | | 49 | 9 |
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| 41.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.16104868913857678 | | totalSentences | 267 | | uniqueOpeners | 43 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 130 | | matches | | 0 | "Then the greeting arrived, short" | | 1 | "Once Eva had bitten them" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 130 | | matches | | 0 | "She set it by the" | | 1 | "It had not healed into" | | 2 | "Her straight black hair lay" | | 3 | "His signet ring flashed silver" | | 4 | "Her shoulders still held the" | | 5 | "Her eyes still met first," | | 6 | "It was a good chair," | | 7 | "He left one near Eva," | | 8 | "His boot scraped the floor" | | 9 | "Her eye caught a red" | | 10 | "It had once been a" | | 11 | "He did not look at" | | 12 | "His signet ring clicked twice" | | 13 | "They landed as business, and" | | 14 | "Her fingertip left a damp" | | 15 | "She looked at the glass," | | 16 | "He poured without asking." | | 17 | "She did not drink." | | 18 | "His silver ring caught the" | | 19 | "He did not listen, and" |
| | ratio | 0.177 | |
| 6.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 130 | | matches | | 0 | "The rain had laid the" | | 1 | "Aurora Carter came through the" | | 2 | "She set it by the" | | 3 | "It had not healed into" | | 4 | "Her straight black hair lay" | | 5 | "Silas Blackwood stood behind the" | | 6 | "His signet ring flashed silver" | | 7 | "Her shoulders still held the" | | 8 | "Silas took the satchel, lifted" | | 9 | "Someone waited in the last" | | 10 | "The booth sat under a" | | 11 | "A woman had her back" | | 12 | "Aurora stopped with her hand" | | 13 | "The woman's hair used to" | | 14 | "A charcoal coat lay over" | | 15 | "The name came out lower" | | 16 | "Eva turned her head." | | 17 | "Her eyes still met first," | | 18 | "Aurora pulled off her satchel" | | 19 | "Aurora sat across from her." |
| | ratio | 0.908 | |
| 38.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 130 | | matches | | | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 2 | | matches | | 0 | "Black-and-white photographs watched the bar: men in caps, women in coats, streets paved with faces that had lost their names." | | 1 | "The booth sat under a bookshelf that looked only like a bookshelf until one hand found the hidden iron latch." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |